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Can a data-rich environment help identify the sources of model misspecification?

Monti, Francesca (2015) Can a data-rich environment help identify the sources of model misspecification? CFM discussion paper series (CFM-DP2015-05). Centre For Macroeconomics, London, UK.

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Abstract

This paper proposes a method for detecting the sources of misspecification in a DSGE model based on testing, in a data-rich environment, the exogeneity of the variables of the DSGE with respect to some auxiliary variables. Finding evidence of non-exogeneity implies misspecification, but finding that some specific variables help predict certain shocks can shed light on the dimensions along which the model is misspecified. Forecast error variance decomposition analysis then helps assess the relevance of the missing channels. The paper puts the proposed methodology to work both in a controlled experiment - by running a Monte Carlo simulations with a known DGP - and using a state-of-the-art model and US data up to 2011.

Item Type: Monograph (Discussion Paper)
Official URL: http://www.centreformacroeconomics.ac.uk/Home.aspx
Additional Information: © 2015 The Authors
Divisions: Centre for Macroeconomics
Subjects: H Social Sciences > HB Economic Theory
JEL classification: C - Mathematical and Quantitative Methods > C3 - Econometric Methods: Multiple; Simultaneous Equation Models; Multiple Variables; Endogenous Regressors > C32 - Time-Series Models
C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation and Selection
Sets: Research centres and groups > Centre for Macroeconomics
Date Deposited: 14 Dec 2017 12:12
Last Modified: 20 Sep 2019 23:23
URI: http://eprints.lse.ac.uk/id/eprint/86320

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